Energy Transition Programme

Long term forecast of the energy transition and the implications for our industries

Our approach

To establish an independent view of the energy transition, DNV GL develops its own energy transition model. The system dynamics model we are using includes population, productivity and energy efficiency considerations. It looks at a dozen separate energy supply and demand sectors and helps us establish an independent outlook through to 2050. 

The results are presented in an annual global and regional analysis of the world’s energy system, as well as separate outlooks for each of our key industries. 

As part of this approach we are analyzing energy transition drivers. These include general drivers – such as policies and efforts supporting technology developments – as well as drivers in major trends such as sustainability, digitalization and urbanization. We are also investigating business model changes, like the sharing and circular economy models. Finally, we consider the major transition barriers, such as energy security and protectionism, short-termism, and lack of coordination and predictability in targets, policies and incentives. 

The energy transition research combines the long-term focus of DNV GL’s Group Technology and Research team with the customer centricity and the technological competence of our business areas: Maritime, Oil & Gas, Energy, Business Assurance and Digital Solutions.


Energy Transition Dynamics 

The ongoing energy transition is certain, but its exact speed and impact is not. 

The Energy Transition Dynamics project team combines expertise in public policy, economics, engineering and behavioral science and encapsulates its own insights, and that of colleagues into a flexible simulation model. The methodology used, System Dynamics, enables us to reflect the interconnections and feedbacks between and within various parts of the global and regional energy system. Depicting ten regions, driven by in-house analyses of productivity and thus economic growth, energy demand and its transition to alternative fuels is forecasted by deep understanding of underlying technologies and corresponding cost learning curves on the demand side.  Similarly, differential learning cost curves for various fossil and renewable energies – frequently supported and/or hindered by public policy generates a race towards ever cheaper extraction and production of energy. 

Our approach is distinguished by several features, not commonly seen in global energy projections.  With respect to content, we include also how ships, such as crude and products carriers, coal bulk, LPG and LNG ships will be affected when oil and gas extraction changes as a function of new technologies and a changing demand. Our method also ensures that expert views are reflected on par with empirical and econometric forecasting.  This way, our model’s decision making reflects the real world:  When real decision making is cost optimized, so is our model.  When real-world decision makers use simple decision heuristics, so does our model. In line with the System Dynamics modelling tradition, the approach is one with the endogenous view that most of the energy transition is internally driven through a web of self-correcting and self-amplifying forces.  Even public policy not only influences the energy system dynamics, but it also responds to it.  

The programme refines the Energy Source Mix Explorer (EMSX) suite of simulation models.  This suite enables us to better understand how any organization, such as a company or a nation, will be affected by the changes in the energy system. Typical key metrics are revenues, taxes, employment and market shares.  

Our researchers